Most AI training does not survive contact with real work. Sloa was built to change that.
Within a single organization one person has barely used AI, another writes with it daily, and a third is already building agents. A fixed curriculum cannot serve all three. Most AI education is still a video library, a one-off workshop or a generic prompting tutorial — and people finish it without becoming meaningfully better at using AI.
Sloa combines a predefined competency framework with adaptive execution. The framework defines where learners should eventually arrive. The adaptive system determines the most effective path for each person, based on prior knowledge, role, technical depth, goals and how they actually perform.
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Competency areas
From AI fundamentals through applications and agents to production systems and strategy.
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Personalization layers
Individual, role, industry and organization context shape every learning path.
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Fixed learning paths
Structure comes from the framework, not from one prescribed sequence of lessons.
AI fundamentals
What AI, machine learning and generative AI can and cannot do
Foundation
Practical AI usage
Prompting, research, writing, analysis, images and code
Core
Building AI applications
APIs, chatbots, RAG, vector databases and multimodal systems
Build
AI agents
Tool use, planning, reflection and multi-step workflows
Build
Technical foundations
Neural networks, transformers, NLP and computer vision
Depth
Production AI
Evaluation, fine-tuning, monitoring, safety and deployment
Depth
AI in organizations
Identifying use cases, managing projects, strategy and risk
Applied